Prosoft provides big data services and solutions that enable organizations unlock business value and make intelligent decisions quickly.

We define three layers for our Big Data solutions:

  1. Big Data Platform: Engine for processing huge amounts of data in diverse formats. Hadoop and in-memory databases serve as such platforms.
  2. Analytics Software: Libraries equipped with high-level data analysis functions and data mining packages.
  3. Consulting: Frameworks and design best practices to offer solutions for each operation challenge.

Prosoft offers a full range of big data services, from consulting and strategy definition to infrastructure maintenance and support, enabling our clients to get vital insights from previously untapped data assets. We apply a proprietary big data framework combined with popular open-source technologies like Apache Hadoop, Spark, Flink, Storm, and Kafka as well as machine learning and deep learning algorithms to deliver a comprehensive tool set for storing, processing, and analyzing large quantities of data.

Prosoft’s big data services enable organizations to:

  • Find the right approach to collecting and connecting with data.
  • Connect the dots across data silos for generating actionable insights.
  • Develop and implement big data solutions across all business verticals.
  • Identify and resolve big data security risks ahead of time.
  • Maintain and manage big data services with ease.

“We help organizations garner the right customer insights leading to newer revenue sources through cross sell and up sell driving profitability. From strategy road map, tech evaluation, and proof of concept to platform customization and implementation, our experts are always at hand to help you navigate all stages on your big data journey.”

As part of our Big Data services, we also offer an approach that supports Big data integration with Data Warehouse (DWH) to become a hybrid structure. In this hybrid model, the highly structured optimized operational data remains in the tightly controlled data warehouse, while the less structured and unstructured data that is highly distributed and subject to change in real time is in a data lake controlled by a Hadoop-based (or similar NoSQL) infrastructure.  Today’s online business landscape generates increasing volumes of data in data sources; and it is inevitable that operational and structured data will have to interact in the world of big data, where the information sources have not (necessarily) been cleansed or profiled. Increasingly, organizations are understanding that they have a business requirement to be able to combine traditional data warehouses with their historical business data sources with less structured and vetted big data sources. Our hybrid offering supporting traditional and big data sources can help to accomplish these business goals.

“Combining historical business data with less structured data from big data sources (machine data, transactional data, public data, etc.) provides for uncovering hidden data patterns and correlations and getting insights that can drive business-improving actions, which is a huge step towards accurate forecasting and boosted profit.”

Our big data experts are great at using big data tools and technologies to turn your meaningless datasets into actionable insight and a competitive advantage – enabling you answer new questions; discover fixes to issues you haven’t noticed before; uncover new possibilities for your business. Then your analytics become the foundation of data-driven decisions that enable your organizations to replace best-guess decisions with real-time intelligence.”

Our Data Lake service enables organizations to define, design, and develop the capabilities of dealing with data of any size, shape, and speed. We help our clients empower their developers, data scientists, and analysts with the right tools to leverage quintillions of bytes of data. We enable organizations to:

  • Create a reservoir for enterprise, social, and device information.
  • Develop a scalable storage, compute, and access data layer.
  • Enable data governance and enterprise-wide access controls.
  • Reduce the time to access and locate data to accelerate preparation and reuse.
  • Build and test customized analytics models with speed.
  • Track and trace data lineage to ensure data quality and deliver reliable insights.

We develop custom Big Data management and analytics solutions, empowering your team to analyze high-speed information in real-time, producing relevant predictive correlations and patterns. Starting from understanding your big data to designing robust data architecture on cloud or premise or hybrid cloud, we help enterprises in their digital transformation journey. Our Big Data consulting team of Data Engineers, Data Analysts and Data Scientists empower such companies to overcome big data challenges and build a modern unified data platform with ease. Equipped with specialized Big Data skill sets, our teams adopt a strategic approach towards building Data Analytics & BI solutions on major cloud platforms.

Our Data Engineering and Big Data Services include the following:

  • Reviewing your current data architecture to analyze data sources and define data lakes or DWHs
  • Building data pipelines that gather, process, store, and help access data
  • Cleaning, processing, and transforming data into usable formats for model development
  • Consult on selecting the best fitting open source or proprietary big data analytics tools and products for your project
  • Helping choose among big data platforms for managing your data infrastructures, such as Cloudera, AWS (Amazon Web Services), Microsoft Azure, Google BigQuery, Teradata, SAP, IBM, Oracle, and more

Technology Stack

Our team’s Big Data technology expertise include the following:



Big Data Processing Frameworks

Data Pipeline/Integration

Analytics DBs

Advanced Analytics and Visualization

Data mining

Big Data Pipeline

We build data pipelines on top of a scalable architecture that support growth in data size, data sources, and data types without any drop in efficiency and encourage our clients to take advantage of cloud platforms that provide the ability to scale automatically without human intervention, such as AWS and Oracle.

Our experienced Data Engineers design and utilize tools and services – API, CLI, Terraform, SDK (Java, Python, Ruby, Go) …, Cloud Infrastructure Events, functions-as-a-service, etc. – from leading technology vendors and system integrators to build big data pipelines that are typically split into the following stages:

1.  Data Sources

We recognize that without quality data, there’s nothing to ingest and move through the pipeline. Data sources are the wells, lakes, and streams where organizations first gather data. SaaS vendors support thousands of potential data sources, and every organization hosts dozens of others on their own systems. Therefore, as the first layer in a data pipeline, data sources are key to our design

2.  Ingestion

In this phase, we load data from various sources, such as streams, APIs, logging services, or direct uploads. This data can originate from various devices or applications (mobile apps, websites, IoT-devices, and so on) and commonly has a nonbinary but semi-structured or unstructured format, such as CSV or JSON.

3.  Data Lake

This phase is a processing step in which we hold raw data in a highly scalable, highly available, and inexpensive repository.

4.  Preparation and Computation

In this phase, we extract data, transform it, and load it (ETL). Data preparation means a cleansed and conformant data format as an output for further processing. We do ETL as a batch or as a stream. Computation of data lets our data scientists create models from data; they might use incoming data to train machine learning models. Apache Spark and the Hadoop ecosystem are leading products we use.

5.  Data Warehouse

In this phase, we store data in a structured format in a database. For Big Data, storage is only possible after ETL processing.

6.  Presentation

In this phase, we present data in analytics or business intelligence tools, commonly using graphics and providing filtering and dashboarding capability.

Big Data Reporting

Prosoft offers design, architecture, deploy the choice of Hadoop distributions, Time series databases, MPP databases, data processing using Hive, Sqoop, Pig, Spark, develop the solutions using Java, Scala, Python or Ruby on MongoDB, Cassandra, HBase, or others on AWS, Azure, Oracle or bare metal deployments. Prosoft can help implementing Data Lakes, perform the relational analysis using RedShift, Vertica or other systems, develop analytics with Spark, R, Python or others and do Visualization, business intelligence reporting using Tableau, Xplenty, Knime, Openrefine, Sisense or other systems. Prosoft can help organizations develop Preventive, Predictive and Prescriptive Analytics on the platform deployed or can develop custom built Sales Analytics, Service Analytics, Distribution Analytics or can even develop competitive analysis depending the data available. All these advanced analytics supports the decision-making process easy for increasing operational efficiency and to lower the costs.

“We help our clients reduce revenue leakages and boost bottom line productivity using advanced data science solutions.”

With our high-level Business Intelligence expertise, we convert comprehensive amounts of unstructured, semi-structured and structured data into visualized, customizable reports enhanced with interactive dashboards that make analytics manageable even for non-tech users.

Our implementation of big data analytics projects typically involves the following stages:

  1. Business Case Evaluation
  2. Data Identification
  3. Data Acquisition & Filtering
  4. Data Extraction
  5. Data Validation & Cleansing
  6. Data Aggregation & Representation
  7. Data Analysis
  8. Data Visualization
  9. Utilization of Analysis Results

Prosoft Analytics Expertise

Descriptive Analytics

With the right tools and an extensive technology stack, we provide you with pertinent insights for customer behavior, operational processes, fraud prevention, risk management and more.  With our expert-level business intelligence, you will have better decisions, including forecasting, strategic planning, optimizing, performance analysis, trend analysis, customer insight, budget controlling, financial reporting and more

We empower your data scientists and analysts with the right tools to analyze historical data to derivate insight into past consumer behavior.

We provide illustrative dashboards to include past, present and predictive data.

We offer domain-based market research to provide quick insights.

Predictive & Advanced Analytics

Companies need to be more agile and responsive and our Big data analytics offerings enable companies to inspect, clean, and model data to draw valuable, business-oriented conclusions.

Our dedicated team of data engineers have the diverse domain expertise and in-depth strategizing experience. We leverage innovative engineering technologies to solve data-intensive challenges.

We devise solutions that facilitate generating detailed insight through augmented intelligence and by leveraging the potential of modern predictive analytics resulting in higher RoI and productivity.

Mobile Business Intelligence

We design mobile apps that are native and responsive across multiple mobile devices to allow users to interact and get actionable insights with minimal clicks and enabling them make informed decisions on the road. Top level executives can now monitor key performance indicators on the fly using their respective mobile devices and act immediately as required.

Data Visualization and Reporting

In order for data to be usable and meaningful, it needs intelligent and informative representation.

We offer consulting services in big data visualization, interpreting visually trends, patterns, and outliers as well as spot relationships between thousands of business variables, providing answers to your business problems.

Dashboards, reports, charts and alerts are designed in a way to be presented on mobile devices to make quick and informed decisions in real time, thereby helping organizations to increase the efficiency of their field executives to maintain zero response time for customer queries.

We deliver mobile business intelligence as web apps and as well as native apps on iOS & android platforms.

Our data visualization experts can profile your data through creative charts, infographics, heat maps and so on to help you unlock hidden value, uncover new insights, generate custom reports and create your very own decision support system.


“Visualizing big data analytics allows business leaders to quickly make sense of information and provides real-time insights to identify new opportunities and help companies stay ahead of the competition. “

Big Data Analytics Advisory

With our expertise on various Hadoop distributions, MPP, time series databases, cloud storage systems and other emerging technologies, Prosoft can help organizations take advantage of industry best technologies by providing advisory services on Big Data Analytics. Prosoft can help with design, architecture and deployment, recommendation of best practices and even develop a proof of concept or proof of value based on business needs through advisory services.


Big Data Analytics Support Services

Proosft offers Hadoop (any distribution) administration, monitoring, configuration of Hadoop, Visualization tools, Analysis tools, Business Intelligence tools, Performance monitoring and load the data as required to Hadoop environment, platform health check through Big Data Analytics Support Services. We offer Support Services Engagements in many flexible engagement models.


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